Search Results (160)

Metagenomic next-generation sequencing (mNGS) is transforming infectious disease diagnostics by enabling simultaneous, hypothesis-free detection of a broad array of pathogens—including bacteria, viruses, fungi, and parasites—directly from clinical specimens such as cerebrospinal fluid, blood, and bronchoalveolar lavage fluid. Unlike traditional culture and targeted molecular assays, mNGS serves as a powerful complementary approach, capable of identifying novel, fastidious, and polymicrobial infections while also characterizing antimicrobial resistance (AMR) genes. These advantages are particularly relevant in diagnostically challenging scenarios, such as infections in immunocompromised patients, sepsis, and culture-negative cases. Despite its potential, mNGS remains underutilized in clinical microbiology due to persistent gaps between its technical capabilities and routine diagnostic adoption. This review addresses key translational challenges that limit the broader implementation of mNGS, especially in resource-constrained and critical care settings. We provide a comprehensive overview of the entire workflow—from sample processing and host DNA depletion to sequencing platforms and downstream bioinformatics—and highlight sources of variability, including contamination, human DNA interference, and inconsistencies in resistance gene annotation. Additionally, we explore the ethical, legal, and privacy implications of host genomic data, as well as economic and regulatory obstacles hindering mNGS integration into standard clinical practice. To illustrate clinical relevance, we examine real-world evidence from large-scale trials such as MATESHIP, GRAIDS, DISQVER, and NGS-CAP. Finally, we outline future directions involving artificial intelligence, multi-omics integration, cloud-based analytics, and portable sequencing technologies for point-of-care diagnostics. By addressing both current limitations and emerging innovations, this review offers a translational framework for integrating mNGS into precision diagnostics and infection management across diverse healthcare environments. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by integrating smart diagnostic devices with cloud computing and real-time data analytics. The emergence of infectious diseases, including COVID-19, underscores the need for rapid and decentralized diagnostics to facilitate early intervention. Traditional centralized laboratory testing introduces delays, limiting timely medical responses. While point-of-care molecular diagnostic (POC-MD) systems offer an alternative, challenges remain in cost, accessibility, and network inefficiencies. This study proposes an IoMT-based architecture for fully automated POC-MD devices, leveraging WebSockets for optimized communication, enhancing microfluidic cartridge efficiency, and integrating a hardware-based emulator for real-time validation. The system incorporates DNA extraction and real-time polymerase chain reaction functionalities into modular, networked components, improving flexibility and scalability. Although the system itself has not yet undergone clinical validation, it builds upon the core cartridge and detection architecture of a previously validated cartridge-based platform for Chlamydia trachomatis and Neisseria gonorrhoeae (CT/NG). These pathogens were selected due to their global prevalence, high asymptomatic transmission rates, and clinical importance in reproductive health. In a previous clinical study involving 510 patient specimens, the system demonstrated high concordance with a commercial assay with limits of detection below 10 copies/μL, supporting the feasibility of this architecture for point-of-care molecular diagnostics. By addressing existing limitations, this system establishes a new standard for next-generation diagnostics, ensuring rapid, reliable, and accessible disease detection. Full article

Galactic cosmic rays (GCRs), composed of protons and atomic nuclei, are accelerated in sources such as supernova remnants and pulsar wind nebulae, reaching energies up to the PeV range. As they propagate through the interstellar medium, their interactions with dense regions like molecular clouds produce secondary particles, including gamma-rays and neutrinos. In this study, we use the Geant4 Monte Carlo toolkit to simulate secondary particle production from GCR interactions within the Perseus molecular cloud, a nearby star-forming region. Our model incorporates realistic cloud composition, a wide range of incidence angles, and both hadronic and electromagnetic processes across a broad energy spectrum. The results highlight molecular clouds as significant sites of multi-messenger emissions and contribute to understanding the propagation of GCRs and the origin of diffuse gamma-ray and neutrino backgrounds in the Galaxy. Full article

The deep integration and application of artificial intelligence to organic chemistry are propelling the development of organic chemistry synthesis laboratories toward an intelligent automated laboratory model characterized by “hardware + software + AI”. This paper systematically explores the overall framework of AI-driven intelligent laboratories for organic chemistry synthesis, achieving automation and flexibility through standardized experimental integration workstations and intelligent scheduling and collaborative management of experimental resources. By leveraging multimodal databases, the integration of large models, machine learning, and other AI technologies enables AI-driven closed-loop intelligent chemical experiments, including product prediction, molecular retrosynthetic planning, and synthesis reaction optimization. The paper proposes a cloud-based shared operational model for chemical laboratories, aiming to achieve socialized sharing and intelligent matching of experimental resources, thereby facilitating the accumulation and sharing of chemical experimental data to promote the intelligent development of organic chemistry synthesis experiments. Practical cases of building intelligent chemical laboratories are shared, providing paths for technology implementation in constructing the next generation of automated and intelligent chemical laboratories. Full article

Background/Objectives: Endometrial cancer (EC) is the sixth most common cancer among women worldwide, and its global incidence has significantly increased over the past three decades. Despite its substantial burden, comprehensive reviews of EC-related research remain limited. This study employs topic modeling to analyze and classify recent research trends in EC. Methods: We identified studies related to endometrial carcinoma published between 2019 and 2023 in PubMed, Web of Science, and the Cochrane Library. The search was conducted using the following terms: endometr* AND (neoplasm* OR cancer* OR carcinoma*) NOT endometriosis. Word clouds were constructed and topic modeling was performed to analyze research activity. Results: A total of 2188 studies were selected, and 11,552 terms were extracted. High-frequency and TF-IDF-weighted keywords included ‘cancer’, ‘risk’, ‘survival’, ‘stage’, ‘tumor’, ‘surgery’, and ‘OS.’ Topic modeling analysis identified ten clusters, categorized as follows: ‘Gynecologic cancer’, ‘Surgical staging’, ‘Therapeutic efficacy’, ‘Diagnosis’, ‘Surgical management’, ‘Multimodal treatment’, ‘Molecular treatment’, ‘Risk factors’, ‘Survival’, and ‘Hormonal regulation.’ Conclusions: This study highlights that recent research on EC has primarily focused on surgical decision making, outcome prediction, and patient survival. Future studies should place greater emphasis on multimodal treatment and prevention—particularly through the identification of risk factors—as well as on improving patients’ quality of life. Full article

The removal of per- and polyfluoroalkyl substances (PFAS) from global aquatic environments is an emerging issue. However, little attention has been paid to addressing accumulated PFAS through their removal. This study demonstrates the encapsulation of perfluoroalkyl carboxylic acids (PFCAs) within polymer microspheres that dissolve in supercritical carbon dioxide (scCO₂). PFCAs were effectively captured by a hindered amine-supported monomer, 2,2,6,6-tetramethyl-4-piperidyl methacrylate (TPMA), in methanol (MeOH) through a simple acid-base reaction. The PFCA-loaded TPMA underwent dispersion polymerization in MeOH in the presence of poly(N-vinylpyrrolidone) (PVP) as a surfactant, producing microspheres with high monomer conversions. The microsphere size depended on the molecular weight and concentration of PVP, as well as the perfluoroalkyl chain length of the PFCAs. X-ray photoelectron spectroscopy (XPS) revealed that the perfluoroalkyl chains migrated from the interior to the surface of the microspheres when exposed to air. These surface perfluoroalkyl chains facilitated dissolution of the microspheres in scCO₂, with cloud points observed under relatively mild conditions. These findings suggest the potential for managing PFCA-encapsulated microspheres in the scCO₂ phase deep underground via CO₂ sequestration. Full article

In the present work, we suggest a new approach for studying the equilibrium states of an hydrodynamic isothermal turbulent self-gravitating system as a statistical model for a molecular cloud. The main hypothesis is that the local turbulent motion of the fluid elements is purely chaotic and can be regarded as a perfect gas. Then, the turbulent kinetic energy per fluid element can be substituted for the temperature of the chaotic motion of the fluid elements. Using this, we write down effective formulae for the internal and total the energy and for the first principal of thermodynamics. Then, we obtain expressions for the entropy, the free energy, and the Gibbs potential. Searching for equilibrium states, we explore two possible systems: the canonical ensemble and the grand canonical ensemble. Studying the former, we conclude that there is no extrema for the free energy. Through the latter system, we obtain a minimum of the Gibbs potential when the macro-temperature and pressure of the cloud are equal to those of the surrounding medium. This minimum corresponds to a possible stable local equilibrium state of our system. Full article

The disk of the Milky Way fills the interstellar medium in the form of discrete clouds, many (∼30) light-years across. The average density of this medium is 1 hydrogen atom per cm³ (Oort limit), in the clouds—several dozen atoms, and between the clouds about 0.01 atoms per cm³. It is well documented that physical properties of individual interstellar clouds are evidently different using high-resolution spectroscopic observations of slightly reddened stars. We prove here that the 5780/5797 strength ratio is nearly constant for all slightly reddened targets. The reason for this phenomenon remains unknown. All optically thin clouds are apparently of σ-type. The question of at which value of color excess one may expect a ζ-type cloud remains unanswered. For some (unknown) reason ζ-type clouds are always relatively opaque and contain a lot of molecular species. In all slightly reddened objects we always observe σ-type intervening clouds, almost free of simple molecules. Full article

Background: Navify^® Mutation Profiler (Navify MP) is a cloud-based, tertiary analysis software that provides curation, annotation, and reporting of somatic genomic alterations and biomarker signatures identified by next-generation sequencing. The Navify MP software leverages Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists (AMP/ASCO/CAP) Somatic Variant Classification Guidelines to provide information on detected somatic genomic variants and associated therapies according to region-specific approvals. Methods: This validation study assessed the accuracy of the Navify MP software and curation process for hematologic malignancies as compared to expert opinion. A total of 86 variants derived from hematologic malignancies (including myeloid and lymphoid leukemias, B cell lymphomas, and multiple myeloma) were used to contrive 12 VCF files. The VCFs were made up of the following classes of genomic alterations: single nucleotide variants, small insertions and deletions, fusions, and copy number alterations. Of the 86 variants, 42 were Tier IA, and 44 were non-Tier IA, based on AMP/ASCO/CAP classification. The study was performed at four sites with seven software users (molecular genetics experts). Results: Tier classification agreement between Navify MP and expert user assignment was 91.34% for Tier IA and 95.02% across all hematologic variants. The agreement on associated therapies for the Navify MP-classified Tier IA hematologic variants was 99.08%. Conclusions: Navify MP is a robust automated solution for genomic variant reporting of hematologic malignancies and remains up to date with evolving regional approvals and medical guidelines. Full article

Industrial hemp (Cannabis sativa L.) was investigated as a sustainable biosorbent for removing Congo Red (CR) and Remazol Brilliant Blue R (RBBR) from wastewater. The unmodified hemp biosorbent exhibited moderate but practically relevant sorption capacities (4.47 mg/g for CR; 2.44 mg/g for RBBR), outperforming several agricultural waste materials. Kinetic studies revealed rapid uptake, with CR following pseudo-first-order kinetics (t₁/₂ < 15 min) and RBBR fitting the Elovich model, indicating heterogeneous surface interactions. Equilibrium data showed CR adsorption was best described by the Temkin isotherm (R² = 0.983), while RBBR followed the Langmuir model (R² = 0.998), reflecting their distinct binding mechanisms. Thermodynamic analysis confirmed spontaneous (ΔG° < 0), exothermic (ΔH° ≈ −2 kJ/mol), and entropy-driven processes for both dyes. Molecular docking elucidated the structural basis for performance differences: CR’s stronger binding (−7.5 kcal/mol) involved weak noncovalent interaction arising from partial overlap between the π-electron cloud of an aromatic ring and σ-bonds C-C or C-H (π-σ stacking) and hydrogen bonds with cellulose, whereas RBBR’s weaker affinity (−5.4 kcal/mol) relied on weak intermolecular interaction between a hydrogen atom (from a C-H bond) and the π-electron system of an aromatic ring (C-H∙∙∙π interactions). This work establishes industrial hemp as an eco-friendly alternative for dye removal, combining renewable sourcing with multi-mechanism adsorption capabilities suitable for small-scale water treatment applications. Full article

The increasing complexity of cloud service composition demands innovative approaches that can efficiently optimize both functional requirements and quality of service (QoS) parameters. While several methods exist, they struggle to simultaneously minimize the number of combined clouds, examined services, and execution time while maintaining a high QoS. This novelty of this paper is the chemistry-based approach (CA) that draws inspiration from the periodic table’s organizational principles and electron shell theory to systematically reduce the complexity associated with service composition. As chemical elements are organized in the periodic table and electrons organize themselves in atomic shells based on energy levels, the proposed approach organizes cloud services in hierarchical structures based on their cloud number, composition frequencies, cloud quality, and QoS levels. By mapping chemical principles to cloud service attributes—where service quality levels correspond to electron shells and service combinations mirror molecular bonds—an efficient framework for service composition is created that simultaneously addresses multiple objectives in QoS, NC, NEC, NES, and execution time. The experimental results demonstrated significant improvements over existing methods, such as Genetic Algorithms (GAs), Simulated Annealing (SA), and Tabu Search (TS), across multiple performance metrics, i.e., reductions of 14–33% are observed in combined clouds, while reductions of 20–85% are observed in examined clouds, and reductions of 74–98% are observed in examined services. Also, a reduction of 10–99% is observed in execution time, while fitness levels are enhanced by 1–14% compared to benchmarks. These results validate the proposed approach’s effectiveness in optimizing service composition while minimizing computational overhead in multi-cloud environments. Full article

Aqueous zinc-ion batteries (AZIBs) have attracted interest for their low cost and environmental friendliness. Two bipolar organic materials with different degrees of conjugation, pPMQT and pNTQT, were rationally designed and synthesized as cathode candidates for AZIBs based on 4,4′-diaminotriphenylamine (TPA), 2,7-diaminoanthraquinone (AQ), and two anhydrides. This molecular design features an increased conjugation and electron cloud density, thereby improving charge transport kinetics, specific capacity, and cycling stability. In comparison with pPMQ and pNTQ (n-type), pPMQT and pNTQT demonstrate better electrochemical characteristics. In this work, pNTQT shows outstanding performance. It exhibits an initial capacity of 349.79 mAh g⁻¹ at 0.1 A g⁻¹ and retains a specific capacity of 190.25 mAh g⁻¹ (87.6%) after 5000 cycles at 5 A g⁻¹. In comparison, pNTQ demonstrates a specific capacity of only 207.55 mAh g⁻¹ at 0.1 A g⁻¹, and after 5000 cycles at 5 A g⁻¹, its capacity retention rate is only 81.2%. At the same time, both pPMQT and pNTQT polymer films demonstrate attractive electrochromic (EC) properties, displaying reversible color transitions from yellow to dark blue in the UV–visible spectrum. This work lays the foundation for the further development of triphenylamine-based polyimide materials for application in AZIBs and electrochromism. Full article

The blueberry fruit (Vaccinium corymbosum L.) exhibits a high content of bioactive compounds, including anthocyanins, that can be used as pigmenting agents, but they are mixed with sugars, which can hinder their utilization. The objective was to evaluate the use of aqueous two-phase extraction aided by centrifugation to separate bioactive compounds, particularly anthocyanins, from blueberry fruits, considering the reduction of sugars, for their use as pigmenting agents in a food product. A mixture of trisodium citrate (Na₃C₃H₅O(COO)₃; Na₃Cit) and polyethylene glycol ([HO-(CH₂CH₂O)n-CH₂OH]; poly (ethane-1,2-diol); PEG) with a molecular weight of 4 kDa was used. Based on the cloud point method, a binodal diagram was developed. After the evaluation of several systems with composition located on a tie line, conditions were identified to form biphasic systems with phases of equal volume. Passive sedimentation for 0, 15, and 30 min, followed by centrifugation and also passive sedimentation for 24 h without centrifugation, were evaluated. A system with 17.73% Na₃Cit, 21.33% PEG, 30 min of passive sedimentation, and 15 min of centrifugation at 2940× g produced an extract with a high concentration of soluble phenols (0.353 mg/mL) and anthocyanins (0.202 mg/mL) and, likewise, high antioxidant activity (910.0 mmol gallic acid equivalents per mL), with reduced sugar content, which demonstrated to have the potential to pigment food beverages with a reddish tone. Full article

Gravitational fragmentation of a protoplanetary disk is considered a possible mechanism for the formation of planets and brown dwarfs. In this process, transitory objects are formed that are known as clumps, which are compact gas–dust condensations with a size of several astronomical units. The contraction of these clumps to planetary sizes via the dissociation of molecular hydrogen or tidal downsizing can ultimately lead to planet or brown dwarf formation. Here, we present a comprehensive numerical and statistical study of the clump properties in protoplanetary disks formed from cloud cores of similar mass (0.9–1.0 $M_{\odot }$). We focus on possible differences in their characteristics depending on the metallicity of the parental disk. We show that notable differences can be expected in the clump characteristics in terms of their number, internal energetics, mass, and distance to the star. For all metallicities considered, the propensity to forming planets or brown dwarfs via disk fragmentation is challenged by large amounts of gravitationally unbound clumps. We conclude that giant planet formation via disk fragmentation is possible down to 1/100 solar metallicity but it should be a rare outcome. Brown dwarf formation via disk fragmentation is possible only down to 1/10 solar metallicity. Our results stand for similar masses of the central star on the order of the Sun. Full article

Supercritical CO₂ (scCO₂) is a versatile solvent for polymer processing; however, many partially fluorinated polymers exhibit limited solubility in neat scCO₂. Organic cosolvents such as toluene can enhance polymer–solvent interactions, thereby improving solubility. The cloud point behavior of poly(2,2,2-trifluoroethyl methacrylate) (poly(TFEMA)) at 3 wt% concentration in scCO₂–toluene binary mixtures was investigated over a temperature range of 31.5–50 °C and toluene contents of 0–20 wt%. Solvent mixture densities were estimated using the Altuin–Gadetskii–Haar–Gallagher–Kell (AG–HGK) equation of state for CO₂ and the Tait equation for toluene. For all compositions, the cloud point pressure was observed to increase linearly with temperature. The cloud point pressure decreased monotonically with increasing toluene concentration and at the highest concentration of 20 wt% was reduced by approximately 40% in comparison to neat scCO₂. The addition of toluene lowered the solvent density, but the increase in solvent–solute molecular interactions resulted in the observed decrease in cloud point pressure. Toluene is shown to be an effective cosolvent for dissolving poly(TFEMA) in scCO₂, offering a promising approach to lowering operating pressures in fluoropolymer processing. Our results provide valuable phase behavior data for designing scCO₂-based extraction, impregnation, and particle formation processes involving poly(TFEMA). Full article